A verification-first agentic workflow for SciML surrogate discovery adds per-candidate, machine-checkable physics audits that expose a causality failure an error-only baseline misses.
MIONet: Learning multiple-input operators via tensor product.SIAM Journal on Scientific Computing, 44(6):A3490–A3514
2 Pith papers cite this work. Polarity classification is still indexing.
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GICON combines graph message passing with example-aware positional encoding to enable in-context operator learning that outperforms classical operator learning on air quality prediction tasks across regions.
citing papers explorer
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Physics-Audited Agentic Discovery in Scientific Machine Learning
A verification-first agentic workflow for SciML surrogate discovery adds per-candidate, machine-checkable physics audits that expose a causality failure an error-only baseline misses.
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Graph In-Context Operator Networks for Generalizable Spatiotemporal Prediction
GICON combines graph message passing with example-aware positional encoding to enable in-context operator learning that outperforms classical operator learning on air quality prediction tasks across regions.